对核电厂设备在线监测与诊断，有助于实时掌握其运行状况，预测可能发生的故障，从而提高核电厂的安全性与经济性。本工作针对核电厂旋转设备上常见的轴承缺损类故障展开研究，采用能量算子对轴承的振动信号进行包络解调，将故障特征频率从噪声与高频信号中发掘出来。为能够自动确定带通滤波器的中心频率，提出用频带方差作为相应的指标，该指标具有在共振频率处取得最大值的特性。利用实验数据验证本工作的可行性与有效性，结果表明本工作提出的方法可有效监测轴承状况并正确诊断出其相应的故障类型。%By on-line monitoring the equipments in nuclear power plant (NPP) ,their working conditions could be known timely and the faults could be predicted ,so that the safety and economy of NPP can be improved .The monitoring and diagnosis of bearing faults in rotatory machines in NPP were studied . The energy operator method was adopted for the envelope demodulation of the vibration signals , w hich could find the fault characteristic frequencies from the noises and modulating signals .To automatically determine the center frequency of the band-pass filter ,the frequency band variance was proposed as an index ,w hich achieved the maximum around the resonant frequency .T he feasibility and validity of the proposed method were verified by the experimental data . The results show that the conditions of the bearings are effectively monitored ,and fault types are correctly diagnosed.
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